The present invention relates to the field of atmospheric sciences, in particular, atmospheric correction in remote sensing.
Remote sensing implies gathering information of an object or phenomenon using sensing devices that are not in direct contact with that object. An example is a sensing device or a sensor, which detects and measures the radiation from a target through an atmosphere to estimate the location and or spectral signature of the target. As a beam of radiation propagates through the atmosphere it undergoes wavelength dependent modification by the atmospheric constituents and elements that it encounters. The spectral characteristics of the beam change due to losses of energy to absorption, gains of energy by emission, and redistribution of energy by scattering and optical refraction. These atmospheric induced modifications cause degradation of the remotely sensed images and can alter the apparent spectral signature of the target being observed.
Atmospheric correction may be used to provide more accurate and reliable results by removing atmospheric effects. Atmospheric constituents and elements of interest include clouds, water vapor, aerosols, and atmospheric gases, all of which are known to often absorb and/or scatter the target radiation signal before it reaches the sensor. Profiles of these disruptive atmospheric elements have to be specified properly in order to perform atmospheric correction accurately. Current atmospheric correction systems use a single vertical profile to represent the atmosphere over a large region.
Radiative transfer is the physical phenomenon of energy transfer in the form of electromagnetic radiation. Radiative transfer models or codes are known in the art to calculate radiative transfer of electromagnetic radiation through an atmosphere. Atmospheric profiles are needed as weather inputs to radiative transfer models such as MODerate Resolution Atmospheric TRANsmission (MODTRAN) to calculate the proportion of target radiation that propagates through the atmosphere to the sensor. Radiative transfer codes make the assumption that the operational atmosphere is plane parallel and horizontally invariant. As a result, many atmospheric correction tools require the user to select a weather report or model based vertical profile to represent atmosphere over a several Kilometer path. The implicit assumption has been that a profile can be used to generate an atmospheric correction that is representative over an area of hundreds of square Kilometers. This assumption and the use of a single vertical representative path have been proven false for events that occur in environments such as weather fronts and low pressure systems. This will be explained below using FIGS. 1-2 for conventional atmospheric correction systems.
FIG. 1 illustrates a scenario 100 for a conventional atmospheric correction system.
As illustrated in the figure, scenario 100 includes a ground 102, a target 104, and a sensor 106.
FIG. 1 shows an example where target 104 and sensor 106 are at two different altitudes over a horizontal distance 114. As illustrated in the figure, a line 112 represents line of sight (LOS) between target 104 and sensor 106. A point 118 represents an altitude 110 from ground 102 looking straight through the atmosphere from sensor 106. Sensor 106 is at an altitude 116 from ground 102. A line 108 represents the difference in altitudes between target 104 and sensor 106.
Conventional atmospheric correction systems use a single vertical profile to represent the atmosphere over horizontal distance 114. To generate an atmospheric profile, conventional atmospheric correction systems assume a homogeneous atmosphere along line of sight 112 and only take in to account the difference in altitude 108 between target 104 and sensor 106 with no horizontal variability. This assumption and the use of a single vertical representative path have been proven incorrect for events that occur in environments such as weather fronts and low pressure systems. This will be explained further using FIG. 2.
FIG. 2 illustrates a detailed view of the signal path between the target and the sensor of conventional atmospheric correction systems.
As illustrated in the figure, assuming that sensor 106 is collecting emissions from target 104 represented by signal 204. A vertical plane 202 represents operational atmosphere over a large region between target 104 and sensor 106, which is assumed to be plane parallel and horizontally invariant by conventional atmospheric correction systems. In reality, as signal 204 travels along line of sight 112, it gets refracted because of the in-homogeneities in the operational atmosphere as represented by horizontal lines inside vertical plane 202. The refraction of signal 204 is represented by signal 206, which gets further refracted and so on. Signal 204 is sequentially refracted by segments 206, 208, 210, 212, 214 and 216 before it reaches sensor 106. Conventional atmospheric corrections systems use only a single vertical profile to perform refraction calculations. Although it is used to calculate refractivity associated with changing altitude along line of sight 112, the conventional approach neglects horizontal inhomogeneities in the atmosphere between target 104 and sensor 106 that can substantially alter the rate of refraction. This neglect can produce large errors that significantly affect the quality of the data retrievals.
Conventional atmospheric correction tools mostly collect data from numerical weather prediction models and use a climatological relationship to generate atmospheric data along the line of sight. Some conventional atmospheric correction tools may also use radiosonde data or climatology itself to generate atmospheric data along the line of sight. It has been proven through analysis that the assumption of horizontal uniformity for weather profile is not applicable for events or observations that occur close to weather fronts, low pressure systems, or land/sea breezes near coastlines and it can be shown that these types of weather profile are significantly variable in terms of their impact on atmospheric correction.
As discussed above with reference to FIGS. 1-2, conventional atmospheric correction systems may not accurately represent the operational atmosphere of their line of sight because the geometry for the path of data being collected usually travels between two different altitudes over long horizontal distances with highly variable atmospheric conditions. The errors, resulting from the in-homogeneities in the operational atmosphere along the slant path can result in incorrect assessment of atmospheric compensation value. Atmospheric correction errors such as these can lead to incorrect intelligence assessments that are based on poor retrievals of technical intelligence.
What is needed is an atmospheric correction system, which can generate atmospheric profiles from the data along the actual target to sensor slant-range path based upon the target to sensor geometry.